Download Toward a Better Integration of Ecological

Roundtable
Toward a Better Integration
of Ecological Principles into
Ecogeoscience Research
DANIEL C. ALLEN, BRADLEY J. CARDINALE, AND THERESA WYNN-THOMPSON
Interdisciplinary research in the fields of ecohydrology and ecogeomorphology is becoming increasingly important as a way to understand how
biological and physical processes interact to affect some of the world’s most pressing environmental problems; however, much of this research is
based on overly simplistic assumptions about ecological systems. Here, we provide a road map for the integration of some ecological principles into
these budding fields of research that warrant future study. We focus on three basic principles of ecology that should have important implications
for ecohydrology and ecogeomorphology: Biological traits exist in a distribution due to species diversity, biological traits are adaptable and
dynamic through time, and dynamically coupled relationships between species and their environments create biotic–abiotic feedback cycles.
We develop several general hypotheses that incorporate these principles and can help guide future ecohydrology and ecogeomorphology studies.
Keywords: ecogeomorphology, biogeomorphology, ecohydrology, hydroecology, ecosystem engineers
A
lthough much of the biological and physical
sciences have developed as distinct disciplines, we
increasingly recognize that global change research requires
that we work at the nexus of biological and physical systems
to solve many of the world’s most pressing environmental
problems. Therefore, an increasing number of interdisciplinary fields are rapidly evolving—fields such as ecogeo­
morphology and ecohydrology—in which the relationships
between biological communities and geomorphologic and
hydrologic processes are investigated. Research coupling
ecology and the geosciences has increased exponentially
over the past decade, as is evidenced by the growth in the
number of articles published, the founding of new interdisciplinary journals, and increased funding opportunities
and awards (figure 1). Despite the exponential growth, the
utility of research in ecogeomorphology and ecohydrology
is often limited by a rather simplistic view of how biological processes influence the physical environment. Indeed,
in a recent National Research Council report (NRC 2009),
it was argued that a better understanding of Earth system
processes could be achieved through a broader incorporation of ecological principles and researchers were called on
to more fully investigate how biota influence Earth surface
processes. In part, this call was motivated by the fact that
purely physical models are often insufficient to predict geophysical processes.
There are many examples in the literature in which
researchers have been misled by not having an accurate integration of biological and physical processes. For example,
paleoclimatic studies in the 1990s failed to explain past climate events with purely physical models (Foley et al. 1998).
But with information on how boreal forest vegetation affects
albedo, models were able to reproduce temperature changes
associated with the Quaternary ice age and the Holocene
warming. Vegetative effects on albedo, soil moisture, and
evapotranspiration were also necessary in order to model
the African monsoon of the early Holocene, when the
Saharan desert was covered by extensive grasslands, savannas, and lakes (Foley et al. 1998). But such is also the case
in research related to hydrology and geomorphology. In the
1980s, it was widely believed that vegetation was a passive
component of the hydrologic cycle and that the Earth system was driven exclusively by ocean–atmosphere dynamics,
with little influence from terrestrial vegetation (Kabat et al.
2004). Of course, we now know that one cannot realistically
describe hydrological processes without including vegetation information (Gordon and Huxman 2007). Therefore, to
prevent similar failures in the future, we should learn from
these experiences and better integrate biology with geo­
morphologic and hydrologic processes.
Here, we discuss three ecological principles that could
address some common limitations in the current state of
BioScience 64: 444–454. © The Author(s) 2014. Published by Oxford University Press on behalf of the American Institute of Biological Sciences. All rights
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doi:10.1093/biosci/biu046
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444 BioScience • May 2014 / Vol. 64 No. 5
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Roundtable
that incorporate these ecological principles. The intended
audience of this article is ecogeoscience researchers who
use both experimental and modeling approaches, and we
include some thoughts about how we can increase collaboration and dialogue between modelers and experimentalists to
produce a more quantitative understanding of the relationship between the Earth’s biological and physical processes.
Figure 1. Productivity of ecohydrology and
ecogeomorphology research from 1990 to 2011, measured
by the cumulative number of articles published (the
solid line), ecogeosciences interdisciplinary journals (the
dashed line), US National Science Foundation (NSF)
awards (the dotted line), and the total amount of funds
awarded (the dashed and dotted line, in tens of thousands
of US dollars). The research articles and NSF awards
were identified by searching the Web of Science and the
NSF Web site, searching for articles and awards with
terms related to ecohydrology and ecogeomorphology
research (the search string was ecogeomorph* OR
biogeomorph* OR eco-geomorph* OR bio-geomorph*
OR ecohydrolog* OR hydroecolog* OR eco-hydrolog* OR
hydro-ecolog* OR ecohydraul* OR eco-hydraul*). The
ecogeoscience interdisciplinary journals were identified
using Journal Citation Reports to locate journals in both
ecology (searching for ecology or biology) and geoscience
(searching for geosciences, multidisciplinary, or water
resources) categories. Note the log scale on the y-axis.
ecogeoscience research, from an ecological perspective: (1) a
distribution of biological traits exists in nature due to species
diversity, (2) biological traits are dynamic, and (3) dynamic
coupling between biological traits and geophysical processes
produce dynamic feedback cycles. For the purposes of this
article, we refer to ecogeomorphology and ecohydrology
collectively as the ecogeosciences. Although we acknowledge
that, in the development of any research field, it is often
good practice to start simply and add complexity piecemeal,
it is our hope that, by addressing some ecological limitations
early on, we can help guide future research on the dynamics
between biological communities and geophysical processes.
Because reviews of ecohydrology and ecogeomorphology
are already present in the literature (e.g., D’Odorico et al.
2010a, Reinhardt et al. 2010), we do not offer an exhaustive
list of important ecological–geophysical interactions. Rather,
we use specific case studies as platforms to discuss how
we can address these limitations and to generate hypotheses for ecohydrology and ecogeomorphology research
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Ecological principle 1: Biological traits in nature are
variable because of species diversity, and variation
can have impacts that differ from the mean value of
those traits
Perhaps the most striking aspect of the Earth is its diversity
of life, which is often reflected in the diversity of traits that
organisms possess. All biological responses to and effects on
physical processes are ultimately governed by species traits.
Species traits are a foundational concept in community
ecology and affect how species coexist (Macarthur 1958),
compete with one another (Tilman 1981), or facilitate one
another (Stachowicz 2001). When species vary in biological
traits, it follows logically that they should also vary in their
responses to and effects on physical processes. However, in
the vast majority of studies in ecogeosciences, the fact that
a distribution of biological traits exists in nature has been
ignored. This is not to say that researchers in the ecogeosciences do not consider biological traits in their studies,
nor are we suggesting that these researchers are not aware
that traits vary among species. Indeed, there are numerous
examples of studies or models in which different parameter
values are considered for different types of organisms or ecosystems (e.g., the photosynthetic rate of a grassland versus
that of a forest). Even so, in the overwhelming majority of
studies, biological variation per se has not been considered,
nor has it been acknowledged that the systems studied are
characterized by multiple, coexisting species that all have
unique trait values.
Ecologists have found that we cannot take a simple mean
value of an ecological parameter and expect that mean to
accurately represent the influence of organisms on ecosystemlevel processes. Rather, the variation around that mean can
have stronger effects on a given process than does the mean
itself. There is now abundant evidence that biodiversity
and its corresponding trait variation exert direct control
over key ecosystem processes, which are strongly linked to
physical processes, such as the production of plant biomass
(Cardinale et al. 2011). In the physical sciences, a similar phenomenon can be found in studies in which the effects of the
height of roughness elements (e.g., a protruding stone or animal shell on a stream bottom) on near-bed flow patterns are
examined. De Marchis and Napoli (2012) modeled turbulent
channel flows over two surfaces with the same mean roughness height (often used as a parameter in hydraulics models)
but allowed the surface geometry of one surface to vary
while the other remained constant (i.e., the surfaces shared
the same mean roughness height, but one had a larger variance). The result was that the more-varied surface produced
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Table 1. General hypotheses that integrate basic ecological principles into ecohydrology and ecogeomorphology research.
Ecological principle
Hypothesis
(1) A distribution of biological
traits exists in nature
H1: Biodiversity increases the likelihood of a system containing a unique species that has disproportionate
effects on a given process, such that a more diverse system will have stronger effects than a less diverse
system would.
H2: Biodiversity increases the likelihood of a system containing complementary traits (which produce additive
biodiversity effects through niche differentiation) or synergistic traits (which produce nonadditive biodiversity effects
through interactions), such that a more diverse system will have stronger effects than a less diverse system would.
(2) Biological traits
are dynamic
H3: The expression of biological traits is phenotypically plastic such that changes in the physical environment
can lead to changes in trait expression that alter hydrologic and geomorphic processes.
H4: Biological traits can change rapidly because of evolution, on short timescales of just a few generations.
Therefore, the evolution of biological traits that influence hydrologic and geomorphic processes can evolve
rapidly, as well, which can affect hydrology and geomorphology.
(3) Bidirectional relationships
generate feedback cycles
H5: Landscapes and biological communities coevolve and influence each other over time, and accurately
describing feedback cycles is necessary to capture the dynamic coupling of their relationships.
a markedly different flow pattern, which suggests that the
simple mean roughness height does not accurately represent
roughness effects (De Marchis and Napoli 2012). Variation
around the mean of physical parameters (e.g., precipitation
variables) in ecogeoscience models is frequently addressed
through the use of stochastic models and Monte Carlo simulations, which randomly assign parameter values on the basis
of the distribution of physical properties observed within a
system (e.g., Petrie and Brunsell 2012). Therefore, although
ecogeoscience research has incorporated variation in physical variables, it is still common practice to represent biological characteristics with a mean value (e.g., the plant canopy
height of a grassland or a forest). Although some researchers
have made steps in the right direction, such as considering
the effects of variation in vegetation cover (canopy heights
and canopy gaps) as roughness elements (Okin 2008), the
explicit links to variation in biological community structure
or biodiversity are still not made in these studies. Here, we
argue that the variability of biological variables should also
be considered in ecogeoscience research in order to better
describe the relationships between biological and physical
systems.
Because biological traits are variable among species, the
total number of species and traits present can have strong
implications for community effects on ecosystems. One
current paradigm in the field of ecology is that biodiversity
affects ecosystem processes as diverse as biomass production, flower pollination rates, and prey suppression. These
effects can be quite large, as impacts of biodiversity loss can
rival the effects of climate change, nutrient pollution, and
invasive species (Hooper et al. 2012). However, there is a
dearth of studies in which researchers have examined how
biodiversity might influence physical processes, although we
consider it plausible.
When more species are present in an ecosystem, there is
an increased likelihood that a unique species with especially
strong impacts on a given process will be present (H1 in
table 1). If that species then comes to dominance over others,
the more species that are present in an ecosystem, the more
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likely it is that that high-performing species will enhance
ecosystem-level processes. In ecogeomorphology, we know
that certain species (i.e., ecosystem engineers) can have especially strong influences on landscape evolution (Jones 2012).
In fluvial systems, some plant species play important pioneering roles as ecosystem engineers in river channel evolution. Plants, such as Salix spp., which resist uprooting during
floods, regenerate vegetatively from flood-transported fragments and tolerate a wide range of water levels are central
to the development of pioneer landforms (e.g., islands) in
rivers (Gurnell et al. 2012). In turn, these pioneering plant
species alter flow patterns in ways that encourage sediment
deposition, which provides new habitat for other species
to colonize. Therefore, some species have disproportionate
impacts on physical processes precisely because biological
traits are variable, and a more diverse system is more likely
to contain and become dominated by such a species. Thus,
species-specific trait effects can produce biodiversity effects
on ecosystems.
A second way in which biodiversity affects natural processes is that, when more species are present, the likelihood of complementary or synergistic traits’ being present
increases (H2 in table 1). A few studies have shown that
the interactive effects of biodiversity can affect physical
processes. Cardinale and colleagues (2002) manipulated the
diversity of net-spinning caddisfly larvae, which build individual silk nets in gravel-bed streams to passively capture the
particulate organic matter on which they feed. When caddisfly larvae were placed in artificial streams, the near-bed
current velocities when all three species were present were
22% greater than the near-bed velocities in streams containing each species in isolation (figure 2). Because the nets of
the caddisfly species differ in size, the biogenic structure
created was more topographically complex (i.e., there was
more variation in surface features), which influenced the
patterns of near-bed water flow. Likewise, Allen and Vaughn
(2011) found that the gravel erosion that occurred during a
simulated high-flow event when multiple freshwater mussel
species were present was 44% greater than the simple mean
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Figure 2. The relationship between species diversity and
physical processes from two experiments, one in which
freshwater mussel biodiversity was manipulated and in
which the amount of gravel eroded (the black dark bars,
in grams; source: The data are from Allen and Vaughn
2011), and in the other, caddisfly larvae biodiversity
was manipulated, and near-bed current velocities were
measured (in centimeters per second; the light bars;
source: The data are from Cardinale et al. 2002). The
horizontal lines indicate the mean value of physical
processes from single species treatments to represent
differences in physical processes when interactions between
species are allowed to occur (long-dashed line, gravel
eroded; short-dashed line, current velocity). The error bars
represent the positive standard error.
of eroded gravel from the isolated single-species treatments
(figure 2), presumably because of the increased flow turbulence created by a more topographically complex surface
from the different shapes and sizes of mussel species and
species differences in burrowing depth. Therefore, after measuring a physical process occurring in the presence of one of
three species in isolation, the mean value of those measurements could not adequately predict that same process when
the three species were present together. Therefore, a second
type of biodiversity effect can be generated by species trait
differences that either complement or facilitate each other.
When we consider the evidence from the large number
of experiments in which the effect of biodiversity on ecological processes has been investigated, there is good reason
to believe that the influence of biodiversity on geophysical
processes may be ubiquitous. Because pioneer biodiversity and ecosystem function studies were focused on plant
communities (Tilman et al. 1997), there has been a great
deal of research in which the relationship between plant
biodiversity and ecosystem functions has been investigated.
For example, in a recent meta-analysis of 574 independent
manipulations of primary producer species richness (terrestrial plants and freshwater algae), Cardinale and colleagues (2011) found strong support for the hypothesis that
biodiversity increases biomass production and the efficiency
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of resource use in ecosystems. The mechanisms producing
these effects (briefly described above) are a result of both
species-specific trait effects (H1 in table 1, or the so-called
selection effect; 122 of 196 cases) and effects of species trait
differences that can complement or facilitate each other (H2
in table 1, or the so-called complementarity effect; 157 of 196
cases). Finally, another question of interest is often whether
a diverse system can outperform its most productive single
species, and Cardinale and colleagues (2011) found that that
this occurred in 37% of the studies (transgressive overyielding; 138 of 375 cases).
Therefore, there is ample evidence that biodiversity can
affect key ecosystem processes that we know are also related
to physical processes. In one diversity manipulation in a tree
plantation, Potvin and Gotelli (2008) found that individual
trees in multispecies plantings showed increases of 30%–
58% in tree basal area when compared with trees in singlespecies plantings. Furthermore, a limited number of studies
suggest that biodiversity may also increase plant water-use
efficiency (Verheyen et al. 2008). Much of the research in the
ecogeosciences has been focused on how plants influence
geophysical processes—relationships that are at least partly
due to some aspect of plant biomass (D’Odorico et al. 2010a,
Osterkamp et al. 2012). For example, plant biomass can affect
geophysical processes as diverse as water infiltration rates,
sediment deposition, and air temperatures (table 2).
There are two field studies that we know of in which a relationship between biodiversity and a geophysical process was
observed, although diversity itself was not directly manipulated. In a comparative field study, Wang and colleagues
(2012) investigated the relationship between plant species
richness (encompassing woody and herbaceous plants) and
soil erosion on plots in an evergreen broadleaf forest that
varied in succession stages, which produced a gradient in
species richness. They found a negative relationship between
species richness and the frequency of surface runoff events,
with the most diverse plots (32 tree species) experiencing
9 runoff events over 3 years, compared with 72 runoff events
in plots with 2 tree species (Wang et al. 2012). Moreover, tree
species richness explained approximately 70% of the variation in surface runoff, as well as sediment and phosphorus
losses (Wang et al. 2012). Although the mechanisms producing this effect are unknown, we know from other studies
that tree biodiversity increases the production of fine root
biomass (Balvanera et al. 2006, Brassard et al. 2013), which
could reduce soil bulk density and increase soil hydraulic
conductivity and organic matter content. Likewise, in an
analysis of an observational data set, Bowker and colleagues
(2010) showed that the biodiversity of a biological soil crust
community in a dryland ecosystem affected the soil’s physical properties, including surface roughening (related to water
infiltration and dust trapping) and soil stability (related to
erosion). In their structural equation model, Bowker and
colleagues (2010) showed that diversity metrics were positively correlated with surface roughening (species richness,­
r = .60) and soil stability (species richness, r = .24; evenness,
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Table 2. Summary of biodiversity effects on aspects of plant communities that have been linked to geophysical processes.
Citations
Plant ecosystem
property
Physical property
Aboveground biomass
Canopy interception of rainfall
Water or wind velocity
Sediment erosion, transport, and
deposition
Water use
Soil moisture
Infiltration, groundwater recharge,
evapotranspiration
Verheyen et al. 2008
D’Odorico et al. 2010a
Riparian woody
biomass production
Large woody debris, biogenic
structure
Sediment erosion, transport, and
deposition
Piotto 2008
Osterkamp et al. 2012
Surcharge (mass added to
stream banks)
Mass wasting
Soil porosity
Soil infiltration rate and capacity
Increase soil cohesion
chemically and physically
Soil erosion, stream or river
geomorphology
Belowground biomass
and associated soil
microbes
Geophysical process
Biodiversity and
ecosystem function
Ecogeoscience
Runoff, infiltration, hydrologic cycle
Cardinale et al. 2011
D’Odorico et al. 2010a
r = .34). Despite the limited number of experiments in which
biodiversity effects on physical processes was observed, the
above examples demonstrate that biological variation can
modify biotic effects on physical processes by 22%–44%
beyond the mean traits of the component species (Cardinale
et al. 2002, Allen and Vaughn 2011). Therefore, failure to
include biological variation into ecogeoscience models and
experiments could potentially mislead our interpretations
and understanding of ecogeoscience.
One important consideration is that the vast majority of
biodiversity and ecosystem function studies are controlled
experiments conducted at small spatial scales, and there is
not as much data about how biodiversity might affect ecosystem and geophysical processes at large scales. However,
the limited number of experiments and syntheses in which
the biodiversity–ecosystem relationship at larger scales were
investigated all suggest that biodiversity effects increase as
a function of scale. In a recent meta-analysis, Griffin and
colleagues (2013) found that the magnitude of biodiversity
effects increases as the spatial and temporal scales of the
biodiversity manipulation increase. In other studies, plant
biodiversity effects over large scales in natural ecosystems
have been examined, and it has been found that biodiversity
increases tree productivity in temperate and boreal forests
across eastern Canada (Paquette and Messier 2011), and
plant biodiversity affected multiple ecosystem functions in
a global survey of 224 dryland ecosystems in all continents
except Antarctica (Maestre et al. 2012). Finally, when considering the importance of three different spatial scales of
biodiversity (α diversity, the number of unique species at a
local scale; β diversity, the number of unique species assemblages in a landscape; and γ diversity, the number of unique
species in a landscape), Pasari and colleagues (2013) found
that, although α diversity had the strongest effects on ecosystem functions that were considered individually, β and γ
diversity had positive effects on ecosystem multifunctionality. It is likely that, as one increases the spatial scale, the trait
448 BioScience • May 2014 / Vol. 64 No. 5
Burri et al. 2011,
Nepf 2012
Simon and Collison
2002
Balvanera et al. 2006
D’Odorico et al. 2010a
Gyssels et al. 2005
variation among species and the niche differences between
species are greatest, such that biological variation is manifest
most strongly at large scales.
Therefore, there is good reason to expect that explicit
incorporation of biological variation in ecohydrology and
ecogeomorphology models could lead to major improvements in our understanding of how biological communities
affect geophysical processes. Physical models that condense
biological impacts down to a single value (e.g., a mean value
of biological traits present in nature; figure 3a) are likely
to produce quantitatively incorrect conclusions and may,
in fact, be qualitatively incorrect, as well (Balvanera et al.
2006, Cardinale et al. 2011). Therefore, we suggest that we
should account for biological variation when studying the
relationships between organisms and geophysical processes
(figure 3b) and hypothesize that variation in biological
traits can produce biodiversity effects on physical processes
(H1 and H2 in table 1).
Ecological principle 2: Biological traits are dynamic
Another fundamental concept in ecology is that biological communities are dynamic in both space and time:
Changing biological traits in nature can result from both
ecological and evolutionary processes. Ecological processes
that lead to changes in biological traits include species
replacements through succession, competition, or invasive
species—processes of species turnover that have already
received considerable attention in ecogeoscience research
(Gillette and Pitchford 2004, Huxman et al. 2005, Horn et al.
2012). However, recent research also suggests that evolution
can occur more rapidly than was previously thought and
on timescales that are relevant to those of ecohydrologic
and ecogeomorphologic processes (Schoener 2011). Yet a
common assumption of researchers investigating temporal
dynamics in ecohydrologic or ecogeomorphic processes is
that the biological traits related to geophysical processes are
static (figure 3c). Because much of this work is relatively
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Figure 3. The state of current ecogeoscience research and suggested future
directions. The focus of ecogeoscience research is to describe the relationship
between a biological factor, β, which interacts with a physical (abiotic) factor,
α, to produce a geophysical process, Π. One example might be soil slope
stability (Π), which is a product of the shear strength of the soil matrix (α)
and the cohesion added to the soil matrix by plant roots (β). In panels (a)–
(f), conceptual illustrations are accompanied by conceptual equations.
(a) Ecogeoscience research generally holds a narrow view of biota and assumes
that biological traits are uniform, focused on the mean value of a biological
factor, μ, and we suggest that (b) ecogeoscience research should embrace the
role of biological variability, σ2, rather than trying to control for it. (c) In
ecogeoscience research, it is often assumed that biological traits are static over
time, t, whereas we argue that (d) ecogeoscience research ought to account
for changes in biological traits over time, as well as changes in the physical
environment. (e) Although biota and geophysical processes are related,
ecogeoscience research tends to be limited to unidirectional interactions of
the effect of one on the other. To fully understand the feedbacks between biota
and geophysical processes, we contend that (f) ecogeoscience research needs
to incorporate an element of time to allow feedbacks to develop in order to
understand how the interactions between physical and biological factors (γ and
δ) affect geophysical processes. Drawings: Jesse Antuma.
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new in ecology, there is not a great
deal of research on how rapid biological trait change can affect geophysical
processes. However, we believe that rapid
trait change is something that researchers should consider in the future of
ecogeoscience research, especially given
how rapidly some organisms are adapting to climate change (figure 3d; Hudson
et al. 2011).
One pathway that can lead to biological traits changing over time is phenotypic plasticity, in which environmental
factors influence changes in the expression of biological traits (i.e., phenotypes).
Therefore, a species or genotype may
express traits differently under different environmental conditions, which
may trigger a change in phenotype. An
organism’s physical environment is one
well-studied factor that can initiate phenotypic change in a plastic trait. For
example, much of current climate change
research is focused on how increased
temperature and atmospheric carbon
dioxide concentrations can alter plant
trait expression. In a long-term carbon
dioxide and ozone enrichment experiment in a temperate US forest, Pregitzer
and colleagues (2008) found that trees
increased belowground carbon allocation
in response to increased carbon dioxide
and ozone, which increased fine root
biomass by more than 50%. In a warming
experiment in the Arctic tundra, Hudson
and colleagues (2011) observed that, after
16 years of 1–2-degree (Celsius) warming, three shrub species and one forb
species responded by increasing in leaf
size by more than 40% and increased in
plant height by nearly 30%. Precipitation
changes are important as well; Hoeppner
and Dukes (2012) documented that
drought increased the growth of deep
roots by 121% in a grassland. Therefore,
if plant traits such as fine root biomass
and leaf size are phenotypically plastic
in response to changing environmental conditions, the hydrologic and geomorphic processes that these plant traits
affect (such as soil erosion resistance and
evapotranspiration rates, respectively;
table 2) can change over time, as well
(H3 in table 1).
A second pathway for biological trait
change over time is evolution. Perhaps
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the most profound impacts of changing biological traits on
geophysical processes are observed in the fossil and geologic
records, because the evolution of land plants had a profound
impact on fluvial processes and sediment deposits. In a
review of changes in alluvial formations when land plants
were evolving and colonizing land, Davies and Gibling
(2010) found that land plant evolution was associated with
increases in the proportion of mudrock and in sandstone
maturity, as well as a decrease in the overall sand grain size.
They also found evidence for the formation of meandering
rivers after the appearance of land plants with rooting systems. Davies and Gibling (2010) suggested that the evolution
of land plants led to a period of landscape evolution that
should be considered one of the most significant geomorphologic changes in Earth history.
However, there is a growing body of evidence showing
that evolution can cause ecologically significant changes
over much shorter timescales than was previously thought
possible (Schoener 2011). Although the question of whether
rapidly evolving biological traits can influence ecohydrologic and ecogeomorphic processes has yet to be vigorously
addressed, there is some evidence to suggest that this could
be a fruitful area of research. For example, the evolutionary
responses of native plants to invasive species are one model
system to study rapid evolution. Dostál and colleagues (2012)
found that native Impatiens noli-tangere evolved differences
in plant size, germination phenology, and phenotypic plasticity, depending on whether a coexisting nonnative species
was present. Moreover, Rowe and Leger (2011) showed
that the native grass Elymus multisetus evolved changes in
root:shoot ratio, root length, and morphology in response
to an invasive grass competitor. In another example, Franks
(2011) showed that the annual plant Brassica rapa evolved
to flower earlier at a cost of decreased water-use efficiency
in response to drought, an adaptive strategy for drought
avoidance. Because plant traits related to water use are likely
to be under high selection pressure, especially under changing precipitation and temperature regimes, the relationship
between the rapid evolution of plant traits and ecohydrologic
processes may be a useful avenue of research. Therefore, the
rapid evolution of plant traits related to water-use efficiency,
plant size, root:shoot ratio, root depth, and morphology
has the potential to affect hydrologic and geomorphologic
processes, considerations that should be addressed in future
research (H4 in table 1). One important directive will be
to investigate the relative magnitude of ecological effects
occurring at different temporal scales, contrasting impacts
from migrations of species over long timescales (e.g., biome
migrations in response to climate change) with the effects of
the short-term evolution of existing species in response to
changing ecological conditions.
Ecological principle 3: From unidirectional feedbacks
to dynamically coupled feedback cycles
The historical view that biomes are primarily a product of
their physical environment has been changing over recent
450 BioScience • May 2014 / Vol. 64 No. 5
decades, because there has been a great deal of emphasis
on how organisms, themselves, act as agents of geomorphic
and hydrologic change (Reinhardt et al. 2010). Although
there is no denying that physical processes have strong
effects on ecological processes, we are beginning to understand that the relationships between biology and Earth
surface processes are dynamically coupled—meaning that
we can observe and document causal relationships in both
directions and that those causal relationships are mutually
dependent. Moreover, studies in which only a unidirectional
relationship has been addressed between physical and biological processes often cannot fully explain the patterns
found in nature. As an example, shrub encroachment into
arid and semiarid grasslands has often been attributed to
climate warming—to climate effects on woody and herbaceous plant physiology—but climate effects on vegetation
alone cannot explain variation in grass–shrub cover at the
landscape scale (Archer 1989). However, once a bidirectional
relationship that includes vegetation effects on microclimate
is considered, the heterogeneous cover of shrubs and grasslands can be explained (D’Odorico et al. 2010b).
In ecology, dynamically coupled relationships are common
and produce feedback cycles, in which dynamically coupled
bidirectional interactions govern process trajectories. This
is something that is also common in the ecogeosciences,
in which feedback cycles describing interactions between
biota and Earth surface processes have been proposed for
some time (Schlesinger et al. 1990). Indeed, we have noticed
that the ecogeoscience literature is increasingly using the
term feedback in papers, but, on closer inspection, these
papers often do not actually demonstrate what an ecologist
would consider a feedback cycle. In many papers, conceptual
models that describe dynamically coupled feedback cycles
are proposed but not quantified (Schlesinger et al. 1990,
Monger and Bestelmeyer 2006, Okin et al. 2006). Still others show a unidirectional relationship between physical and
biological processes that were previously known to operate in the opposite direction (Gillette and Pitchford 2004,
Mueller et al. 2007, Okin 2008). Nevertheless, in ecology, evidence of opposing unidirectional relationships between two
processes is a necessary—albeit insufficient—condition to
quantify a feedback (figure 3e). To demonstrate a feedback,
one must show that two processes are dynamically coupled;
the outcome of process A at time t affects the outcome of
process B at time t + 1 (e.g., figure 3f) and vice versa.
The dynamically coupled relationships between vegetation and river channel geomorphology in anabranching ephemeral rivers in drylands could be described by
a feedback cycle (Tooth and Nanson 2000). For example,
we could apply the relationships among tree abundance,
water velocity, and channel width to the graph in figure 3f,
where α is mean water velocity in the anabranches, β is tree
abundance in the dry river channel, and Π is the average
anabranch width. Anabranch width and water velocity are
related to each other: Given a constant discharge, a wider
channel will be shallower and will have a lower velocity,
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Roundtable
whereas a narrower channel will be deeper and will have
a higher velocity. Anabranch width and tree abundance
are related to each other: The establishment of trees in a
sandy dry riverbed promotes the formation of ridges and
islands within the overall channel, creating anabranches but
decreasing the cumulative cross-sectional flow area. Finally,
vegetation and water velocity are also related: Vegetation
slows water velocity near the vegetation but increases it in
the center of the anabranches away from the vegetation;
however, if the water velocity is high enough, trees can
become uprooted. Therefore, we would expect a dynamically
coupled feedback cycle to occur over time, ultimately reaching a ­semiequilibrium state in which the average anabranch
width does not change much, even though the placement
of ridges and islands may change as vegetation dies and
­colonizes over time.
There have been some efforts to quantify feedback cycles
in ecogeoscience research, particularly in ecogeomorphological research linking feedbacks between vegetation type
and erosion in arid systems. Shrub–grass dynamics and
shrub encroachment in arid systems have been proposed
to be a function of three types of feedback cycles: fire–
vegetation feedbacks, soil erosion–vegetation feedbacks,
and vegetation–microclimate feedbacks (D’Odorico et al.
2012). In the fire–vegetation feedback, a negative feedback
loop promoting shrub encroachment has been proposed
such that decreases in fire frequency increase shrub survival and cover, which decreases grass cover, which further
decreases fire frequency. The erosion–vegetation feedback is
another negative feedback loop proposed to promote shrub
encroachment, in which a loss of grass cover increases
the erosion of fine soil particles, which reduces soil fertility, which then reduces grass cover and promotes shrub
growth. Finally, the vegetation–microclimate feedback loop
mentioned earlier also promotes shrub encroachment, such
that shrub cover increases bare soil, which increases nocturnal soil temperatures, which then increases shrub growth
and survival. However, various attempts to quantify these
feedback cycles have been met with limitations that affect
the generality of the findings of those studies. For example,
Okin and colleagues (2009) developed a simple model that
quantified shrub–grass biomass dynamics. In this model,
grasses had a competitive advantage over shrubs, but a
physical–biological feedback was not modeled. Instead
of modeling erosion explicitly to link decreases in grass
cover with decreases in available soil resources, Okin and
colleagues (2009) modeled the carrying capacity of grass
biomass as a function of the existing grass biomass. This
simplified model does not actually include any terms representing a physical process. D’Odorico and colleagues (2012)
developed this model a bit further and incorporated a single
parameter to represent the strength of a physical–­biological
feedback that may exist, but they still did not explicitly
model any physical process. Moreover, neither of these
models was fit with any ecological or physical data (Okin
et al. 2009, D’Odorico et al. 2012).
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Nevertheless, there are a few cases in which dynamically
coupled feedback cycles have been quantified in ecogeo­
science research, and these efforts have greatly helped our
understanding of the development of landforms over time.
Larsen and colleagues (2007) presented a model for the
ridge and slough morphology of peatlands common in lowgradient lotic wetlands that exhibit spatial heterogeneity
and even a pattern of vegetated ridges. Previous models
were focused solely on peat accretion dynamics, which were
enhanced by vegetation but were unable to predict long-term
ridge-growth dynamics. The model presented by Larsen and
colleagues (2007) relied on dual feedbacks between peat
accretion and sediment transport (from flow pulses) and
was able to produce ridge elevations characteristic of the
ridge and slough formations of the Everglades. By including dynamically coupled relationships in the model, Larsen
and colleagues (2007) were able to accurately predict ridge
development in peatlands. In another study, in which historical photographs were used to document river development
after a catastrophic flood that removed all vegetation from
the floodplain, Corenblit and colleagues (2010) observed a
positive feedback cycle between vegetation and river channel development. Pioneering vegetation (herbs and shrubs)
that grew on bare soil helped to promote landform accretion,
which then promoted the establishment of a dense riparian
forest that was ultimately stable under the current hydrogeomorphologic conditions (Corenblit et al. 2010). Therefore,
studies in which modeling or historical approaches were
used show great potential for testing hypotheses that dynamically coupled feedback cycles generate coevolution between
landscapes and biological communities (H5 in table 1). We
advocate that such efforts be a focus of future research in
ecogeoscience.
In order to develop more-realistic models, we need
more collaboration between modelers and experimentalists. Many of the models in ecogeoscience research are
simplified because the model-building processes can get
overly complicated very quickly as the number of variables
grows, which also increases the uncertainty of the model.
Therefore, the majority of models include simple functions to relate biotic and abiotic functions in order to test
hypotheses and are rarely based on any real data in either
the development or testing phases. As a result, these models are inherently unrealistic and do not provide tangible
results that can be used to accurately predict coupled systems. However, in order for ecogeoscience models to grow
in complexity and realism and to improve in accuracy,
we need more ecologists who are willing to collaborate
with modelers to collect the simple data necessary to validate these simple models. Although collecting this simple
data may not excite ecologists currently exploring morecomplex principles in the field, the development and testing of basic models is necessary, because many of our most
important questions need to be addressed at large spatial
or long temporal scales, which modeling methods are often
better suited to address.
May 2014 / Vol. 64 No. 5 • BioScience 451
Roundtable
addressed by integrating the ecological
principle that distributions of biological
traits exist in nature into ecogeoscience
research in order to understand the
relationship between biological variation and hydrologic and geomorphic
processes. (2) In an era of global ­climate
and environmental change, we do not
know how biotic adaptations to these
changes will affect the performance
of important hydrologic and geo­
morphic processes. This problem can
be addressed by incorporating the ecological principle that biological traits are
dynamic into ecogeo­
science research,
which will allow us to understand and
ultimately predict how species adaptations to global change will affect
hydrologic and geomorphic ­processes.
Figure 4. The relationships between the hypotheses presented in this paper
(3) Given global challenges 1 and 2
and ecological, evolutionary, hydrologic, and geomorphic processes. The solid
above, the physical and bio­logical sysline denotes the influence of ecological principle 1, hypothesis 1 (H1), and
tems of the Earth are changing simultahypothesis 2 (H2). The short-dashed line represents principle 2, hypothesis 3
neously, and the consequences of these
(H3), and hypothesis 4 (H4). The long-dashed lines demonstrate principle 3 and
concurrent changes on dynamically
hypothesis 5 (H5).
coupled feedback cycles relating biota to
hydrologic and geomorphic processes
Conclusions
are unknown. By integrating dynamically coupled feedback
Although we present these three ecological principles sepacycles into ecogeoscience research, we will ultimately be
rately, the reality is that they are likely working in concert,
able to predict how biotic and physical changes will affect
and we do not mean to suggest that the hypotheses in table 1
landscape coevolution and equilibrium states in nature. We
are mutually exclusive. Incorporating all of these principles
discussed several examples of studies in which researchtogether will be important to accurately describing landers are advancing our understanding of the links between
scape evolution, because biological traits and physical varibiological communities and landscape processes by inteables are likely to covary and possibly direct the trajectory of
grating these principles and then proposed hypotheses for
the biological–physical system toward an equilibrium state
future research. With biological communities undergo(figure 4). Therefore, future research is needed in which
ing rapid changes because of biodiversity losses and the
these dynamic interactions and the progression of physical–
introduction of nonnative species and changes in physical
biological systems toward equilibrium states are examined.
processes occurring because of simultaneous altered hydroIndeed, there is a growing body of research in which
logic regimes and climate change, there is a great need
interactions between biology and geophysical processes
for research to advance our understanding of how these
are examined, particularly in the budding fields of ecogeochanges will affect landscape processes.
morphology and ecohydrology. Research in these fields
is increasing in importance as many of our most pressing
Acknowledgments
environmental problems (e.g., water quantity and quality of
Funding was provided by National Science Foundation grant
surface flows) are exacerbated by joint changes in biologino. DBI-1103500 to DCA. We thank Celia Miller, Hanna
cal and physical processes. However, to increase our ability
Naughton, and anonymous reviewers for comments that
to understand these problems, we need to better integrate
improved the manuscript.
ecological principles into ecogeoscience research. We have
suggested three basic ecological principles as future focus
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Daniel C. Allen ([email protected]) is affiliated with the School of Letters
and Sciences at Arizona State University, in Mesa. Bradley J. Cardinale is affiliated with the School of Natural Resources and Environment at the University
of Michigan, in Ann Arbor. Theresa Wynn-Thompson is affiliated with the
Department of Biological Systems Engineering at Virginia Tech, in Blacksburg.
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